Block chain-based document and creative copyright protection method and system

Abstract

The invention discloses a block chain-based document and creative copyright protection method and system. The method comprises the steps of receiving and analyzing a work, and performing originality verification analysis; generating a unique digital fingerprint, encrypting and packaging the unique digital fingerprint into an evidence storage transaction and permanently recording the evidence storage transaction in a block chain network; the evidence storage data is synchronized to one or more external heterogeneous copyright evidence storage platforms or block chain systems to realize cross-domain mutual recognition of ownership information; monitoring network infringement, identifying infringement and generating an early warning report; and responding to the authorization request, calling the intelligent contract, and automatically executing copyright authorization permission. The system comprises a work originality verification module, a credible evidence storage uplink module, a cross-chain mutual recognition gateway module, a dynamic infringement monitoring module and an intelligent authorization execution module. Through adoption of the scheme, the credibility and reliability of binding between the on-chain evidence storage and the off-chain entity works can be remarkably enhanced, a data island between different block chain evidence storage platforms is broken, infringement is monitored in real time, right protection is efficient, and the transaction cost and the manual operation risk are reduced.

Description

Technical Field

[0001] This invention belongs to the field of data security and digital copyright management technology, specifically relating to a blockchain-based method and system for protecting cultural and creative copyrights. Background Technology

[0002] With the booming development of the digital cultural and creative industry, the creation, dissemination, and commercialization of original content are becoming increasingly frequent. Copyright protection has become a core element in safeguarding the rights and interests of creators and the healthy development of the industry. Cultural and creative works encompass various forms such as text, images, audio, and video. While their digital characteristics improve dissemination efficiency, they also bring problems such as difficulties in confirming rights, complex evidence collection for infringement, and opaque authorization chains. Traditional copyright protection mechanisms mainly rely on centralized registration agencies or third-party evidence storage platforms, which have inherent defects such as long registration cycles, high costs, easy data tampering, and lack of cross-platform mutual trust, making it difficult to meet the protection needs of massive, high-frequency, and fragmented cultural and creative content.

[0003] Blockchain-based copyright registration technology, due to its decentralized, immutable, and traceable characteristics, has been widely explored in recent years for the confirmation and protection of digital content rights. This technology attempts to build a credible ownership verification system by recording the work's hash value, creation timestamp, and author information on the blockchain. However, existing blockchain copyright protection solutions still face several technical bottlenecks: First, the binding relationship between on-chain registration and off-chain works is not tight, lacking an effective verification mechanism for the integrity and originality of the work's content; second, the phenomenon of copyright data silos between multiple platforms is serious, with a lack of interoperability between different blockchain systems or registration platforms, making it difficult to verify ownership information across domains; third, infringement monitoring and rights protection responses are lagging, with existing systems mostly providing static registration and lacking dynamic linkage capabilities with content distribution networks and trading platforms; finally, the licensing transaction process lacks the fine-grained control of smart contracts, making it difficult to support complex business needs such as revenue sharing, sub-licensing, and usage scope restrictions. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a blockchain-based method and system for the protection of cultural and creative copyrights. This method and system can effectively solve the problems existing in the background technologies, such as the fragile relationship between on-chain evidence storage and off-chain works, the serious problem of copyright data silos between multiple platforms, the lag in infringement monitoring and rights protection response, and the lack of refined control of the authorization transaction process by smart contracts.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A blockchain-based method for protecting cultural and creative copyrights includes the following steps: Receive electronic files of cultural and creative works and their associated metadata, and verify the originality of the electronic files of cultural and creative works. The associated metadata includes: creator identity ID and creation timestamp; When the originality verification is passed, a unique digital fingerprint is generated based on the electronic file of the cultural and creative work, the creation timestamp, and the creator's identity ID, and a notarization transaction containing the digital fingerprint and encrypted ownership information is constructed. Broadcast the evidence storage transaction to a blockchain system or several external heterogeneous copyright evidence storage platforms to achieve cross-domain mutual recognition of ownership information; Once unauthorized content that highly matches the characteristics of a registered work is identified, an infringement warning notice is generated and sent to the copyright holder.

[0006] This invention also provides a blockchain-based cultural and creative copyright protection system, comprising: The originality verification module is used to receive electronic files of cultural and creative works and their associated metadata, and to verify the originality of the electronic files of cultural and creative works. The associated metadata includes: creator identity ID and creation timestamp. The trusted evidence generation module is used to generate a unique digital fingerprint based on the electronic file of the cultural and creative work, the creation timestamp, and the creator's identity ID when the originality verification is passed, and to construct an evidence storage transaction containing the digital fingerprint and encrypted ownership information. The cross-chain mutual recognition gateway module is used to broadcast the notarization transaction to a blockchain system or several external heterogeneous copyright notarization platforms to complete cross-domain mutual recognition of ownership information. The dynamic infringement monitoring module is used to generate and send an infringement warning notice to the copyright holder when it identifies unauthorized dissemination content that highly matches the characteristics of a work that has been registered.

[0007] Compared with the prior art, the present invention has the following beneficial effects: 1. By introducing a multi-layered automated verification mechanism for the originality of works, the credibility and reliability of the binding between on-chain evidence and off-chain physical works are significantly enhanced, reducing the risk of non-original content being used for evidence storage from the source.

[0008] 2. The designed cross-chain interoperability gateway effectively breaks down data silos between different blockchain evidence storage platforms, enabling seamless transfer and verification of copyright ownership information between heterogeneous systems and improving the interoperability of the entire ecosystem.

[0009] 3. The dynamic infringement monitoring module realizes the transformation from static evidence storage to dynamic rights protection, which can detect online infringement in near real time, greatly shorten the rights protection response cycle, and improve the efficiency of copyright protection.

[0010] 4. The intelligent authorization execution module realizes automated and refined management of authorization transactions through programmable smart contracts, which can flexibly support complex business revenue sharing models and authorization terms, reducing transaction costs and human operation risks. Attached Figure Description

[0011] Figure 1 This is a flowchart of the blockchain-based method for protecting cultural and creative copyrights according to the present invention. Figure 2 This is a scenario diagram of the blockchain-based method for protecting cultural and creative copyrights according to the present invention; Figure 3 This is a schematic diagram of the framework structure of a blockchain-based cultural and creative copyright protection system; Figure 4 This is a schematic diagram of the core principle framework for originality verification and credible evidence generation in this invention; Figure 5 This is a schematic diagram of the multi-level interaction relationship and data flow of the cross-chain mutual recognition gateway module in this invention; Figure 6 This is a logical flow diagram of the dynamic infringement monitoring module in this invention; Figure 7 This is a schematic diagram of the authorization strategy and revenue sharing logic framework of the intelligent authorization execution module in this invention. Detailed Implementation

[0012] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the specific embodiments according to the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments.

[0013] Example 1

[0014] like Figure 1 , 2 As shown, this invention provides a blockchain-based method for protecting cultural and creative copyrights, comprising the following steps: S1. Receive electronic files of cultural and creative works and their associated metadata, and verify the originality of the electronic files of cultural and creative works. The associated metadata includes: creator identity ID and creation timestamp. Specifically, it includes: Extract the cultural and creative features from the electronic files of the cultural and creative works, and compare the similarity between the cultural and creative features and the features of existing works. If the similarity is less than the threshold, the work is considered to have originality; otherwise, originality cannot be determined.

[0015] The extraction of cultural and creative work features from electronic files and the comparison of these features with existing work features require differentiation into different work types, specifically image-based and text-based works. A deep convolutional neural network model is used to extract multi-level features from cultural and creative works. For image works, color histograms, texture features, and SIFT keypoint descriptors are extracted. For text works, word frequency-inverse document, frequency vector, and semantic embedding vector are generated. The cosine similarity and Jaccard index between the features of the creative work and the features of existing works pre-stored in the feature database are calculated to obtain a comprehensive similarity. For example, if the calculated comprehensive similarity index is lower than the threshold τ, τ=0.85, the work is determined to be original.

[0016] If the calculated similarity is below the threshold, the work is deemed to be original, and the originality verification is passed.

[0017] For audio works, including: For audio-based cultural and creative works, the Mel frequency cepstral coefficient feature extraction algorithm is used to extract a 39-dimensional MFCC feature vector from the submitted audio works. The 39-dimensional MFCC feature vector includes: 12-dimensional basic MFCC features, 12-dimensional first-order difference MFCC features, 12-dimensional second-order difference MFCC features, and 3-dimensional energy correlation features. For example, when generating digital fingerprints, an audio feature hash layer is added for audio works. The specific implementation process is as follows: First, the SHA-256 hash value H1a is calculated for the audio file; second, the beat features, chord progression features, and melody outline features of the audio are extracted, and these features are combined to calculate the SHA-256 hash value H1b; finally, H1a and H1b are concatenated with the creation timestamp and creator identity to calculate the final digital fingerprint H2. In the scenario of audio work evidence preservation, a built-in audio metadata mapping table can convert metadata of 15 common audio formats into a standardized format supported by the target chain. The conversion process includes converting the ID3 tag of MP3 format to the MusicMeta standard required by the consortium blockchain, parsing the RIFF block structure of WAV format into standardized fields, and re-encoding the VORBIS annotation of FLAC format into UTF-8 format.

[0018] The similarity between the audio to be detected and the existing works in the music library is calculated using a dynamic time warping algorithm. If the calculated similarity is below the threshold, the work is deemed to be original, and the originality verification is passed.

[0019] S2. When the originality verification is passed, a unique digital fingerprint is generated based on the electronic file of the cultural and creative work, the creation timestamp and the creator's identity ID, and a notarization transaction containing the digital fingerprint and encrypted ownership information is constructed. Specifically, it includes: A two-level nested hash structure is used to calculate the SHA-256 hash value H1 of the electronic file of cultural and creative works. After concatenating the SHA-256 hash value H1 with the creation timestamp T and the creator's identity ID, the SHA-256 hash value H2 is calculated again. The SHA-256 hash value H2 is a unique digital fingerprint. The ownership declaration information is encrypted using an asymmetric encryption algorithm. The ownership declaration information includes at least: the title of the work, the creator's public key, the GPS coordinates of the creation location, and the work's classification code. Generate a notarized transaction containing the unique digital fingerprint and encrypted ownership information.

[0020] S3. Broadcast the evidence storage transaction to a blockchain system or several external heterogeneous copyright evidence storage platforms to complete cross-domain mutual recognition of ownership information; This step can be considered in another different way: The first method involves packaging the digital fingerprint together with the encrypted ownership statement information into a notarization transaction and submitting it to the blockchain network for permanent recording, thus completing the initial copyright notarization of the work. The second method involves using a cross-chain mutual recognition protocol to synchronize the core data of the evidence storage transaction to one or more external heterogeneous copyright evidence storage platforms or blockchain systems, thereby achieving cross-domain mutual recognition of ownership information; this is used to achieve standardized conversion and reliable synchronization of copyright evidence storage data between different blockchain systems. S4. Upon identifying unauthorized dissemination content that highly matches the characteristics of a work already registered, generate and send an infringement warning notice to the copyright holder.

[0021] 1) Initiate a continuous online infringement monitoring process, using content feature matching technology to scan internet content distribution nodes and identify unauthorized dissemination content that highly matches the characteristics of already certified works; 2) When suspected infringing content is detected, an infringement warning notice is automatically generated and sent to the copyright holder, and the chain of evidence of infringement is recorded.

[0022] Preferably, it also includes responding to authorization requests by invoking smart contracts deployed on the blockchain to automatically execute copyright licensing, transaction settlement, and revenue sharing operations based on preset rules.

[0023] Example 2

[0024] like Figure 3-7 As shown, this embodiment provides a blockchain-based cultural and creative copyright protection system, including: The originality verification module 1 is used to receive electronic files of cultural and creative works and their associated metadata, and to verify the originality of the electronic files of cultural and creative works. The associated metadata includes: creator identity ID and creation timestamp. The originality verification module specifically includes a feature extraction unit, a similarity calculation unit, and a decision unit; The feature extraction unit uses a deep convolutional neural network model to perform multi-level feature extraction on the input source file. For image-based works, it extracts the color histogram, texture features, and SIFT keypoint descriptors. For text-based works, it generates the term frequency-inverse document frequency vector and semantic embedding vector. The similarity calculation unit receives the feature vector and calculates its cosine similarity and Jaccard index with the feature vectors of existing works pre-stored in the feature database. The decision-making unit makes a comprehensive judgment on the calculation results based on a preset combination of similarity thresholds. If the calculated comprehensive similarity index is lower than the threshold τ, where τ=0.85, the work is judged to be original.

[0025] The trusted evidence generation module 2 is used to generate a unique digital fingerprint based on the electronic file of the cultural and creative work, the creation timestamp, and the creator's identity ID when the originality verification is passed, and to construct an evidence storage transaction containing the digital fingerprint and encrypted ownership information. When generating the digital fingerprint, the trusted evidence storage on-chain module adopts a two-layer hash nested structure. First, it calculates the SHA-256 hash value H1 of the source file of the work. Then, it concatenates H1 with the creation timestamp T and the creator's identity ID, and calculates the SHA-256 hash value H2 again. H2 is the final unique digital fingerprint on the chain. The evidence storage transaction also includes ownership statement information encrypted with an asymmetric encryption algorithm. This ownership statement information includes at least the title of the work, the creator's public key, the GPS coordinates of the creation location, and the work's classification code.

[0026] The cross-chain mutual recognition gateway module 3 is used to broadcast the evidence storage transaction to the blockchain system or several external heterogeneous copyright evidence storage platforms to complete the cross-domain mutual recognition of ownership information. The data synchronization process implemented by the cross-chain mutual recognition gateway module includes: Listen for new block generation events on the source blockchain; Analyze transaction data related to copyright registration in the block; According to the predefined cross-chain data exchange protocol, the evidence storage data format of the source chain is converted into a format compatible with the target chain. This conversion process involves hash algorithm mapping, timestamp standardization, and adaptation of digital signature verification mechanism. By using relay chain or sidechain technology, the converted data transaction is submitted to the target blockchain network, and the transaction receipt of the target chain is obtained as a synchronization certificate.

[0027] The dynamic infringement monitoring module 4 is used to generate and send an infringement warning notice to the copyright holder after identifying unauthorized dissemination content that highly matches the characteristics of the already registered works.

[0028] The web crawler engine of the dynamic infringement monitoring module adopts a distributed architecture, which can crawl multiple content platforms in parallel. Its content feature matching algorithm is as follows: First, it obtains the H2 hash value and some metadata of the works that have been certified from the blockchain; second, it uses Local Sensitive Hash (LSH) technology to convert the network content to be detected into an LSH signature; finally, by comparing the Hamming distance between LSH signatures, it quickly filters out high-probability suspected infringement content. For the suspected content, it is further verified by the similarity calculation unit.

[0029] The intelligent authorization execution module 5 is integrated into the blockchain network and is used to deploy and manage smart contracts associated with specific copyrighted works. The smart contract has embedded preset authorization rules, revenue sharing logic and execution conditions, and can automatically respond to authorization requests and execute corresponding digital asset transfer and rights licensing operations.

[0030] The smart contract deployed in the smart authorization execution module contains a set of programmable authorization strategy functions. These functions can parse the parameters contained in the authorization request, including the scope of authorization, duration of use, geographical restrictions, distribution channels, and expected transaction amount. According to the preset revenue sharing logic, when the authorized transaction is confirmed, the smart contract automatically divides the transaction amount according to a preset ratio and transfers it to multiple designated revenue sharing addresses. The revenue sharing ratio can be dynamically adjusted, and the adjustment trigger condition is captured by the contract event listener.

[0031] Example 3

[0032] Against the backdrop of the rapid development of the digital cultural and creative industry, original works face core challenges such as difficulty in establishing rights, slow rights protection, and complex authorization management. This embodiment uses a digital art platform as an example to detail the specific implementation process of a blockchain-based cultural and creative copyright protection system. (See also...) Figure 1 The overall architecture of the system comprises five core components: a work originality verification module, a trusted evidence generation module, a cross-chain mutual recognition gateway module, a dynamic infringement monitoring module, and an intelligent authorization execution module.

[0033] like Figure 4As shown, the originality verification module first receives the source file of the digital artwork submitted by the user through the art platform client. This file is a PNG image with a resolution of 4096 x 4096 pixels. The received associated metadata includes the artwork title "Starry Night Fantasy," the creator's digital identity, the creation timestamp (October 26, 2023, 14:30:05), and the artwork classification code (Class A, Visual Artwork). The feature extraction unit uses a pre-trained deep convolutional neural network model, VGG16, to perform multi-level feature extraction on the input image. The specific execution process includes: first, extracting low-level visual features of the image through convolutional layers, including a 256-dimensional color histogram feature, a 512-dimensional texture feature vector extracted using the Local Binary Mode algorithm, and a 128-dimensional SIFT keypoint descriptor vector generated by detecting stable keypoints in the image; then, combining these features into a 2048-dimensional comprehensive feature vector through a fully connected layer. After receiving the feature vector, the similarity calculation unit performs batch similarity calculations with the feature vectors of 850,000 existing works pre-stored in the feature database. The calculation process uses the cosine similarity algorithm and the Jaccard index algorithm in parallel. The cosine similarity algorithm calculates the cosine of the angle between two feature vectors in the vector space, while the Jaccard index calculates the ratio of the intersection to the union of two feature sets. The decision unit makes a comprehensive judgment based on a preset combination of similarity thresholds. The cosine similarity threshold is set to 0.82, and the Jaccard index threshold is set to 0.78. When the calculated comprehensive similarity index, after weighted averaging, is 0.79, which is lower than the preset threshold of 0.85, the system determines that the work has originality and passes verification.

[0034] Upon receiving the originality verification pass command, the trusted evidence generation module immediately initiates the digital fingerprint generation process. (See also...) Figure 5This module employs a two-layer nested hash structure to generate irreversible, unique digital fingerprints. The specific implementation process is as follows: First, the SHA-256 hash value H1 of the source file is calculated, resulting in a 64-bit hexadecimal string. Second, H1 is concatenated with the creation timestamp of October 26, 2023, 14:30:05, and the creator's ID, and the SHA-256 hash value H2 is calculated again. H2 is the final 256-bit unique digital fingerprint uploaded to the blockchain. Simultaneously, the module constructs a notarized transaction containing this digital fingerprint and encrypted ownership information. The ownership declaration information includes the work's title "Starry Night Fantasy," the creator's public key, the GPS coordinates of the creation location (39°54′26″N, 116°23′29″E), and the work's classification code (Class A, Visual Art). This information is encrypted using the RSA asymmetric encryption algorithm with a 2048-bit encryption key. After data encapsulation, the notarized transaction is broadcast to the blockchain network main chain through the node interface, awaiting consensus verification. The blockchain network adopts a proof-of-stake consensus mechanism, with 21 verification nodes verifying the notarized transactions. Once verified, the transaction is packaged into block number 584632, which was generated at 14:35:17 on October 26, 2023. The block hash value is 0x7d4b8e..., and the transaction hash value is 0x9a2c7f..., thus completing the initial copyright notarization of the work.

[0035] Upon detecting a new block generation event on the main chain, the cross-chain interoperability gateway module immediately initiates the cross-chain data synchronization process. (See also...) Figure 6 This module is deployed between the main blockchain network and an external heterogeneous blockchain evidence storage platform. The specific implementation process includes: first, monitoring the generation event of block number 584632 on the main chain; parsing the transaction data related to copyright evidence storage in this block, extracting key fields including digital fingerprint H2, encrypted ownership information, timestamp, and transaction hash value; then, according to the predefined cross-chain data exchange protocol CCEP, converting the evidence storage data format of the source chain into a format compatible with the target chain. This conversion process involves hash algorithm mapping, mapping the SHA-256 algorithm to the SM3 national cryptographic algorithm supported by the target chain; timestamp standardization processing, converting the UNIX timestamp format to the RFC3339 format required by the target chain; and digital signature verification mechanism adaptation, converting the RSA signature scheme to the ECDSA elliptic curve digital signature algorithm supported by the target chain. After the data format conversion is completed, the converted data transaction is submitted to the target blockchain network through relay chain technology. The target chain adopts a consortium blockchain architecture and consists of 15 nodes. After the transaction is submitted, the transaction receipt 0x5e8b3a... of the target chain is obtained as a synchronization certificate. The synchronization completion time is recorded as 14:38:45 on October 26, 2023.

[0036] The dynamic infringement monitoring module initiates a continuous online infringement monitoring process immediately after evidence storage is completed. See also... Figure 7 The module's distributed web crawler engine is deployed across 12 data collection nodes, enabling parallel crawling of multiple content platforms, including 8 mainstream social media platforms, 15 digital art trading platforms, and 6 content sharing websites. The specific implementation process of the content feature matching algorithm is as follows: First, the H2 hash values ​​and partial metadata of the works already certified are obtained from the blockchain; second, using Locality Sensitive Hashing (LSH) technology, the web content to be detected is converted into a 64-bit LSH signature; finally, by comparing the Hamming distance between the LSH signatures, a distance threshold of 8 is set to quickly filter out high-probability infringing content. During the monitoring period, the system detected 7 suspected infringing contents from 3 platforms, with Hamming distances all between 5 and 7. For these suspected contents, the system further uses a similarity calculation unit for precise verification, employing the same feature extraction and similarity calculation process as the originality verification. Ultimately, 5 of the contents were confirmed as infringing copies, with similarities all exceeding 0.92.

[0037] The intelligent authorization execution module automatically triggers the execution process upon detecting an authorization request. See also... Figure 5 The smart contract deployed in this module contains a set of programmable licensing strategy functions. The specific implementation process is as follows: When a commercial organization requests licensing rights to the work "Starry Night Fantasy," the smart contract automatically parses the request parameters, including the scope of licensing as digital media advertising, the usage period from November 1, 2023 to October 31, 2024, geographical restriction to China, distribution channel as an online platform, and the expected transaction amount of 50,000 yuan. Based on the preset revenue-sharing logic, the smart contract automatically divides the transaction amount according to a preset ratio upon confirmation of the licensing transaction. The creator receives 70% (35,000 yuan), the platform's technical service fee receives 20% (10,000 yuan), and the industry association's management fee receives 10% (5,000 yuan). These amounts are transferred in real-time to the designated revenue-sharing address through the smart contract's automatic transfer function. The revenue sharing ratio can be dynamically adjusted. The adjustment trigger condition is captured by the contract event listener. When the cumulative authorized amount exceeds 100,000 yuan, the creator's revenue sharing ratio will be automatically increased to 75%, the platform technical service fee will be adjusted to 15% accordingly, and the industry association management fee will remain unchanged at 10%.

[0038] The infringement warning and evidence preservation mechanism is activated immediately upon confirmation of infringement by the dynamic infringement monitoring module. The system automatically generates an infringement warning notification, which is simultaneously sent to the copyright holder via in-system messages, email, and SMS. The notification includes a link to the infringing content, the time of infringement discovery, information about the infringing platform, and a preliminary summary of evidence. Simultaneously, the system initiates an evidence chain recording process, using a timestamp server to capture and preserve screenshots of the infringing content. The screenshot resolution maintains the original image quality, and the timestamp accuracy reaches the millisecond level. All evidence files are stored in a distributed file system after hash calculation, and the hash values ​​are synchronously recorded on the blockchain as judicial evidence. Within a 24-hour monitoring period, the system detected and processed 5 infringement incidents, reducing the average response time from 72 hours for traditional manual monitoring to 1.5 hours.

[0039] The system performance monitoring and optimization module continuously tracks the operational status of each module. Through performance acquisition agents deployed on each system node, it collects 32 key metrics in real time, including processing latency, memory usage, and network throughput. Data processing latency metrics show that the average processing time for originality verification is 2.3 seconds, the average confirmation time for trusted evidence storage on-chain is 12.7 seconds, the average completion time for cross-chain data synchronization is 8.5 seconds, the infringement monitoring scan coverage reaches 98.5%, and the smart contract execution success rate is 99.8%. The system dynamically adjusts resource allocation based on these metrics. When the backlog of originality verification tasks exceeds 50, it automatically activates the elastic scaling mechanism, expanding the computing nodes from 8 to 16 to ensure that the system response time remains stable within the 3-second limit stipulated in the service level agreement.

[0040] Example 4

[0041] In the field of digital music creation, taking online music platforms as an example, the system's copyright protection process for audio-based creative works has unique implementation characteristics. The originality verification module uses the Mel frequency cepstral coefficient feature extraction algorithm to extract a 39-dimensional MFCC feature vector from submitted audio works, including 12-dimensional basic MFCC features, 12-dimensional first-order difference MFCC features, 12-dimensional second-order difference MFCC features, and 3-dimensional energy correlation features. The similarity calculation unit uses a dynamic time warping algorithm to calculate the similarity between the audio to be detected and existing works in the music library, effectively handling audio comparisons with different playing speeds and rhythms. When the system receives an original electronic music work with a duration of 3 minutes and 45 seconds, the feature extraction process first divides the audio signal into frames, with a frame length of 25 milliseconds and a frame shift of 10 milliseconds, resulting in 6750 audio frames. Then, through pre-emphasis, windowing, fast Fourier transform, Mel filter bank, logarithmic operation, and discrete cosine transform, a 39-dimensional MFCC feature vector is finally generated. The similarity calculation unit compares the feature vector with the features of 1.2 million musical works in the music library, using an improved dynamic time warping algorithm to increase the comparison speed to 3.2 times that of traditional algorithms while maintaining calculation accuracy. The decision unit sets the audio work similarity threshold at 0.88. When the calculated comprehensive similarity is 0.84, the work is deemed to have passed the originality verification.

[0042] The trusted evidence generation module optimizes the digital fingerprint generation algorithm for audio works based on their characteristics. While maintaining a two-layer nested hash structure, an additional audio feature hash layer is added. The specific implementation process is as follows: First, the SHA-256 hash value H1a is calculated for the audio file; second, the beat features, chord progression features, and melody outline features of the audio are extracted, and these features are combined to calculate the SHA-256 hash value H1b; finally, H1a and H1b are concatenated with the creation timestamp and creator's identity identifier to calculate the final digital fingerprint H2. This multi-feature fusion hashing scheme significantly enhances the uniqueness and collision resistance of the digital fingerprint of audio works. During the construction of the evidence storage transaction, in addition to basic metadata, the ownership declaration information also includes professional technical parameters such as an audio sampling rate of 44100 Hz, a bit depth of 24 bits, and two channels. This information is encrypted using the national cryptographic algorithm SM4 with a key length of 128 bits. The encrypted data and the digital fingerprint are packaged together as the evidence storage transaction and submitted to the blockchain network.

[0043] In audio work notarization scenarios, the cross-chain interoperability gateway module primarily addresses the issue of inconsistent audio metadata standards across different blockchain networks. During implementation, this module incorporates an audio metadata mapping table, capable of converting metadata from 15 common audio formats into standardized formats supported by the target chain. When notarized data needs to be synchronized to a consortium blockchain focused on music copyright management, the gateway automatically executes the metadata conversion process. This includes converting MP3 format ID3 tags to the MusicMeta standard required by the consortium blockchain, parsing the RIFF block structure of WAV format into standardized fields, and re-encoding FLAC format VORBIS comments into UTF-8 format. The conversion process maintains data integrity and consistency, ensuring data equivalence before and after conversion through checksums and verifications.

[0044] The dynamic infringement monitoring module, tailored to the characteristics of audio content, employs an infringement detection scheme based on audio fingerprint technology. In practice, the system retrieves the digital fingerprints and feature data of already-certified audio works from the blockchain and collects audio content from major music platforms, video sharing websites, and social media through a web crawler engine. For the collected audio to be detected, noise reduction and standardization are first performed, with a uniform sampling rate of 44100 Hz. Then, its audio fingerprint is extracted using a Landmark-based fingerprint extraction algorithm to extract stable combinations of feature points from the audio spectrum. The fingerprint comparison stage uses inverted index technology, enabling the retrieval of a massive fingerprint database within milliseconds. When suspected content with a matching degree exceeding 92% is found, a manual review process is automatically triggered, while simultaneously preserving a complete chain of infringement evidence.

[0045] In music licensing scenarios, the smart licensing execution module implements a complex copyright revenue-sharing model. When a work involves multiple rights holders such as creators, producers, and singers, the smart contract supports automatic revenue sharing for up to 20 parties. Revenue-sharing rules can be dynamically adjusted based on the licensing type, including differentiated revenue-sharing ratios for different rights types such as mechanical reproduction rights, performance rights, and broadcasting rights. The embedded licensing strategy function in the contract supports condition-triggered revenue sharing. For example, when a single licensing amount exceeds 50,000 yuan, the producer reward clause is automatically activated, allocating an additional 5% of the revenue to the music producer; when the cumulative number of licensing reaches 100, the singer's revenue share automatically increases by 2 percentage points. These complex business logics, through the automated execution of smart contracts, significantly reduce the operational costs of copyright management and the risk of human error.

[0046] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A blockchain-based method for protecting cultural and creative copyrights, characterized in that, Includes the following steps: Receive electronic files of cultural and creative works and their associated metadata, and verify the originality of the electronic files of cultural and creative works. The associated metadata includes: creator identity ID and creation timestamp; When the originality verification is passed, a unique digital fingerprint is generated based on the electronic file of the cultural and creative work, the creation timestamp, and the creator's identity ID, and a notarization transaction containing the digital fingerprint and encrypted ownership information is constructed. Broadcast the evidence storage transaction to a blockchain system or several external heterogeneous copyright evidence storage platforms to achieve cross-domain mutual recognition of ownership information; Once unauthorized content that highly matches the characteristics of a registered work is identified, an infringement warning notice is generated and sent to the copyright holder.

2. The method for protecting cultural and creative copyrights based on blockchain according to claim 1, characterized in that, The process of receiving electronic files of cultural and creative works and their associated metadata, and verifying the originality of the electronic files of cultural and creative works, specifically includes: Extract the cultural and creative features from the electronic files of the cultural and creative works, and compare the similarity between the cultural and creative features and the features of existing works. If the similarity is less than the threshold, the work is considered to have originality; otherwise, originality cannot be determined.

3. The blockchain-based method for protecting cultural and creative copyrights according to claim 2, characterized in that, The step of extracting the cultural and creative work features from the electronic files of the cultural and creative works and comparing the similarity of the cultural and creative work features with the features of existing works specifically includes: A deep convolutional neural network model is used to extract multi-level features from cultural and creative works. For image works, color histograms, texture features, and SIFT keypoint descriptors are extracted. For text works, word frequency-inverse document, frequency vector, and semantic embedding vector are generated. The cosine similarity and Jaccard index between the features of the cultural and creative works and the features of existing works pre-stored in the feature database are calculated to obtain the comprehensive similarity. If the calculated similarity is below the threshold, the work is deemed to be original, and the originality verification is passed.

4. The blockchain-based method for protecting cultural and creative copyrights according to claim 3, characterized in that, The step of extracting the cultural and creative work features from the electronic files of the cultural and creative works and comparing the similarity of the cultural and creative work features with the features of existing works also includes: For audio-based cultural and creative works, the Mel frequency cepstral coefficient feature extraction algorithm is used to extract a 39-dimensional MFCC feature vector from the submitted audio works. The 39-dimensional MFCC feature vector includes: 12-dimensional basic MFCC features, 12-dimensional first-order difference MFCC features, 12-dimensional second-order difference MFCC features, and 3-dimensional energy correlation features. The similarity between the audio to be detected and the existing works in the music library is calculated using a dynamic time warping algorithm. If the calculated similarity is below the threshold, the work is deemed to be original, and the originality verification is passed.

5. The blockchain-based method for protecting cultural and creative copyrights according to claim 1, characterized in that, The step of generating a unique digital fingerprint based on the electronic file of the cultural and creative work, the creation timestamp, and the creator's identity ID, and constructing a notarization transaction containing the unique digital fingerprint and encrypted ownership information, specifically includes: A two-level nested hash structure is used to calculate the SHA-256 hash value H1 of the electronic file of cultural and creative works. After concatenating the SHA-256 hash value H1 with the creation timestamp T and the creator's identity ID, the SHA-256 hash value H2 is calculated again. The SHA-256 hash value H2 is a unique digital fingerprint. The ownership declaration information is encrypted using an asymmetric encryption algorithm. The ownership declaration information includes at least: the title of the work, the creator's public key, the GPS coordinates of the creation location, and the work's classification code. Generate a notarized transaction containing the unique digital fingerprint and encrypted ownership information.

6. The blockchain-based method for protecting cultural and creative copyrights according to claim 1, characterized in that, The cross-domain mutual recognition of ownership information specifically includes: Listen for new block generation events on the source blockchain and parse the transaction data related to copyright registration in the new block; According to the predefined cross-chain data exchange protocol, the notarization transaction format of the source chain is converted into a format compatible with the target chain; The converted notarized transaction is submitted to the target blockchain network via a relay chain or sidechain, and the transaction receipt of the target chain is obtained as a synchronization certificate.

7. The method for protecting cultural and creative copyrights based on blockchain according to claim 1, characterized in that, After identifying unauthorized dissemination content that highly matches the characteristics of already certified works, the following is also included: Initiate a continuous online infringement monitoring process, using content feature matching technology to scan internet content distribution nodes and identify unauthorized dissemination content that highly matches the characteristics of already certified works; When suspected infringing content is detected, an infringement warning notice is generated and sent to the copyright holder, and the chain of evidence of infringement is recorded.

8. The blockchain-based method for protecting cultural and creative copyrights according to claim 7, characterized in that, When a copyright holder receives an infringement warning notice, it also includes: Send an authorization notice to the infringer; Upon receiving a response to the authorization request, the smart contract deployed on the blockchain is invoked to execute copyright licensing, transaction settlement, and revenue sharing operations based on preset rules.

9. A blockchain-based cultural and creative copyright protection system, characterized in that, include: The originality verification module is used to receive electronic files of cultural and creative works and their associated metadata, and to verify the originality of the electronic files of cultural and creative works. The associated metadata includes: creator identity ID and creation timestamp. The trusted evidence generation module is used to generate a unique digital fingerprint based on the electronic file of the cultural and creative work, the creation timestamp, and the creator's identity ID when the originality verification is passed, and to construct an evidence storage transaction containing the digital fingerprint and encrypted ownership information. The cross-chain mutual recognition gateway module is used to broadcast the notarization transaction to a blockchain system or several external heterogeneous copyright notarization platforms to complete cross-domain mutual recognition of ownership information. The dynamic infringement monitoring module is used to generate and send an infringement warning notice to the copyright holder when it identifies unauthorized dissemination content that highly matches the characteristics of a work that has been registered.

10. The blockchain-based cultural and creative copyright protection system according to claim 9, characterized in that, Also includes: The intelligent authorization execution module, integrated into the blockchain network, is used to deploy and manage smart contracts associated with specific copyrighted works. These smart contracts contain preset authorization rules, revenue sharing logic, and execution conditions, and can automatically respond to authorization requests and execute corresponding digital asset transfers and rights licensing operations.

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